Yue Yu
@yue___yu
RS @Meta #superinteligence #Llama | Alum @Tsinghua_Uni @GTCSE | NLP | Large Language Models
We’re at #NeurIPS 2024 in Vancouver, presenting two papers from NVIDIA on advancing state-of-the-art LLM RAG models! ChatQA: Surpassing GPT-4 on Conversational QA and RAG Thu 12 Dec 11 a.m. PST — 2 p.m. PST, West Ballroom A-D #7201 Paper: arxiv.org/abs/2401.10225 RankRAG:…
Introducing RankRAG, a novel RAG framework that instruction-tunes a single LLM for the dual purposes of top-k context ranking and answer generation in RAG. For context ranking, it performs exceptionally well by incorporating a small fraction of ranking data into the training…
🤔 How can we systematically enhance LLMs for complex medical coding tasks? 🚀 Introducing MedAgentGym, an interactive gym-style platform designed specifically for training LLM agents in coding-based medical reasoning! 🧬💻 🎯 Comprehensive Code-based Medical Reasoning…
Excited to present HYDRA 🐉 at #NeurIPS2024! 🚀 Our novel model-factorization framework combines personal behavior patterns 👤 with global knowledge 🌐 for truly personalized LLM generation. Achieves 9%+ gains over SOTA across 5 tasks 🏆 using personalized RAG. Learn more:…
Excited to be at #EMNLP2024 and share our 3 papers on LLM for Health! Let’s chat if you are interested! 📅 Nov 13 10:30-12:00 Session 6 BMRetriever: LLMs for text retrieval MedAdapter: LLMs for medical reasoning 📅 Nov 14 14:00-15:30 Session 12 EHRAgent: LLM Agents for EHR QA
🎉The coolest #CSE school in the world is hiring multiple faculty members! Application link below👇
First time clear mathematical summarization of existing extension!
Long-context is central to models like OpenAI o1, but rare to see in natural data. Extension methods grow context by post-training open LLMs. A tutorial and controlled study of this area of long-context extension. arxiv.org/abs/2409.12181 youtu.be/dc4chADushM
After going through 100s of AI papers in the past couple of weeks, I am noticing the deeper integration of ideas (e.g., Mixture of Million Experts and Internet of Agents) and the utility of simple yet very effective methods (e.g., RouteLLM and RankRAG). If you are looking for…
Incredible results for the RAG world from @nvidia model 👏. Llama3-RankRAG from @nvidia significantly outperforms GPT-4 models on 9 knowledge-intensive benchmarks. 🤯 📌 Performs comparably to GPT-4 on 5 RAG benchmarks in the biomedical domain without instruction fine-tuning on…
🧵1/n LLMs significantly improve Evolutionary Algorithms for molecular discovery! For 18 different molecular optimization tasks, we demonstrate how to achieve SOTA performance by incorporating different LLMs! Learn more in our new paper! Website: molleo.github.io(w/ Code)
🧬 Still using BM25 for biomedical retrieval? Try out BMRetriever! 🔍 Our new series of retrievers enhance biomedical search with various scales (410M-7B). 🔓 Model/Data: huggingface.co/BMRetriever 🌠 Github: github.com/ritaranx/BMRet… #BiomedicalResearch #LLM #Retrieval #OpenScience
So excited to announce our workshop Synthetic Data for Computer Vision at @CVPR on June 18th, 2024. The workshop website: syndata4cv.github.io We welcome submissions! Please consider submitting your work here: openreview.net/group?id=thecv… (deadline: March 15, 2024) #CVPR2024